["itemContainer",{"xmlns:xsi":"http://www.w3.org/2001/XMLSchema-instance","xsi:schemaLocation":"http://omeka.org/schemas/omeka-xml/v5 http://omeka.org/schemas/omeka-xml/v5/omeka-xml-5-0.xsd","uri":"https://johnntowse.com/LUSTRE/items/browse?collection=5&output=omeka-json&page=2","accessDate":"2026-05-22T23:10:37+00:00"},["miscellaneousContainer",["pagination",["pageNumber","2"],["perPage","10"],["totalResults","45"]]],["item",{"itemId":"168","public":"1","featured":"0"},["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3408"},["text","Can better linguistic fluency improve the memorability and credibility of a sentence?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3409"},["text","Hamish Bromley"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3410"},["text","07.09.2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3411"},["text","Processing fluency is often defined as how easy information is to comprehend based on a range of characteristics. One form of processing fluency is linguistic fluency, which refers to how easy a sentence is to interpret, regardless of the information within it. Some research suggests that disfluency can increase the recall of material, but this is contested. Previous studies have also shown that the linguistic fluency of a sentence can be improved with literary devices, such as rhyme, and that this can result in better perceptions of credibility. Research has yet to investigate how alliteration, as an example of linguistic fluency, could improve perceptions of credibility and the memorability of a sentence. This research investigated this by operationalising lists of alliterating and non-alliterating aphorisms, alongside measures of self-reported credibility and memorability, in a between-subjects study. Results of two independent t-tests provided two significant results, suggesting that better linguistic fluency improves the credibility and memorability of a sentence. Implications for researchers, the legal system and advertising are discussed."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3412"},["text","Linguistic Fluency, Alliteration, Advertising,Memory,Credibility"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3413"},["text","Materials \r\nThe preliminary five aphorisms were provided by Astroten with five further aphorisms being added to increase the power of the study. Aphorisms that were selected came from various literary examples, such as quotes from English Literature (Williams, 2011). Alternatively, some aphorisms were created using the definition “a short clever saying that is intended to express a general truth” (Cambridge Dictionary, 2022). The most common alliterating aphorisms, such as “All roads lead to Rome”, were purposefully avoided so that the effect of familiarity had a reduced effect on the memorability self-report. When creating the non-alliterating aphorisms, alliterating words were exchanged for non-alliterating words using a thesaurus so that the change in alliterative properties did not affect the overall meaning. The alliterating and non-alliterating aphorisms were kept divided into two different lists and were counterbalanced in a random order for each participant (Appendix C). Participants were asked to rate the credibility of the aphorisms based on a Likert scale of 1-9, in parallel with the scale used by McGlone and Tofighbakhsh (1999). \r\nParticipants were asked to complete two games of Sudoku as a filler task (Appendix D). The grids were designed so that participants would begin with the easier version and move on to a more challenging version to ensure that the task occupied the full amount of time. Instructions were provided so that those who were unfamiliar with the game were still able to attempt the task. \r\n18 \r\nAdditionally, participants were given a piece of paper with 10 individual sections to write down as many of the aphorisms as they could remember at the end of the study. They were also provided with a pen, and time was kept using a watch. \r\nDesign \r\nThis study used a between-subjects design. This was chosen because there was a strong chance that order effects would impact the results of the memory test in a repeated measures design, due to the similarity between the alliterating and non-alliterating aphorisms. Choosing to mix the aphorisms could have resulted in demand characteristics affecting the results as the disparity between them would have been obvious to the participant. This is something that Oppenheimer and Frank (2008) were also keen to avoid. A quantitative data collection approach was taken because it was judged as the most appropriate way to measure memory, as well as facilitating comparison with other studies that have employed similar methods (McGlone & Tofighbakhsh, 1999; Kara-Yakoubian et al 2022). Participants were either part of the alliterating or non-alliterating aphorisms condition. \r\nProcedure \r\nEthical approval for this study was given by the supervisor of this research, in line with Lancaster University Psychology Department protocols (Appendix E). When participants were approached to take part in the study they were first asked to read an information sheet (Appendix F) followed by a consent form, completion of which evidenced their informed consent to take part. Participation began in a quiet room within the university library. It was ensured that they could spare 20 minutes to take part and that they had turned off their phones before the study began. They began the study by rating each aphorism in \r\n19 \r\ntheir list on a scale of 1-9 based on how credible they thought the aphorism was. The instructions were read to them, but they also had the opportunity to read them if they were unsure (Appendix G). They were then given three minutes to memorise as many of the aphorisms as possible. \r\nFollowing this, participants spent 10 minutes completing the Sudoku, with instructions again read to them and provided on the sheet. Once the 10 minutes were complete the participants were asked to spend five minutes trying to recall as many of the aphorisms from their list as possible by writing them down (Appendix H). They were given one point for every aphorism they could remember correctly. No points were given if the participants could only remember parts of the aphorism. As short-term memory is often described as being 7+/-2 (Miller 1956), memorisation of the entire list would likely have been impossible. Therefore, a prompt was added by reading the participant the first word from each of their aphorisms after three minutes. This aligns more closely with advertising research, which frequently measures prompted recall (Romaniuk, 2006; Charlesworth et al, 2022). On completion, participants were thanked for their participation in the research and given their £5 payment. They were also provided with a debrief sheet (Appendix I) that provided details of resources related to the study and the contact details of the researcher and supervisor. "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3414"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3415"},["text","Excel/xlsx."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3416"},["text","Bromley2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3417"},["text","Cyrus"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3418"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3419"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3420"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3421"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"3422"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3423"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3424"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3425"},["text","Marketing"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3426"},["text","50"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3427"},["text","T-Test"]]]]]]]],["item",{"itemId":"165","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"162","order":"1"},["src","https://johnntowse.com/LUSTRE/files/original/452355f866df5834a5f3cf69981867cb.pdf"],["authentication","633b59c550352193afd39c9b77e8236e"]],["file",{"fileId":"163","order":"2"},["src","https://johnntowse.com/LUSTRE/files/original/11047b373639b050d937897ca4a5716e.pdf"],["authentication","6fc57453ec1e4645a520dc6f8a8c1cd0"]],["file",{"fileId":"164","order":"3"},["src","https://johnntowse.com/LUSTRE/files/original/6f6b6f7a8b6091eaf9a07d56f63eecef.pdf"],["authentication","683f9e69521848a3bb02f903a5483805"]],["file",{"fileId":"165","order":"4"},["src","https://johnntowse.com/LUSTRE/files/original/e52c0d0ba7af2b015e1e1e8e24cf3769.csv"],["authentication","b2aab3de2bfe1035b5ff999baa5d7e0f"]],["file",{"fileId":"166","order":"5"},["src","https://johnntowse.com/LUSTRE/files/original/25b15fafa737967ea654a0cbd84d758b.csv"],["authentication","51c1e8fb52c981d2a0e4eb8351243474"]],["file",{"fileId":"168","order":"6"},["src","https://johnntowse.com/LUSTRE/files/original/c4f2721ff769eddc53538ae8d324d885.csv"],["authentication","fd85883fae12c844cc083286c2b47372"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3345"},["text","The roles of reading motivation and reading strategies in secondary school students’ reading comprehension"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3346"},["text","Anastasija Jumatova "]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3347"},["text","28/09/2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3348"},["text","The aim of the study was to investigate comprehension and inference ability in relation to text genre, reading strategies, intrinsic and extrinsic reading motivation, and gender in mainstream secondary school UK students. Data were collected from a sample of 27 participants; retained data of 9 secondary school students (5 males, 4 females) data were used for the study analysis. These responses were used to inform a simulated dataset for the analysis. The participants completed an online study, which measured their intrinsic and extrinsic reading motivation The Motivation for Reading Questionnaire (MRQ; Wang &amp; Guthrie, 2004), comprehension and inference ability of narrative and expository texts (Currie et al., 2021), and reading strategies (Denton, Wolters, et al., 2015). Due to sample size limitations the decision was made to simulate individual datasets for reading strategies, intrinsic reading motivation, extrinsic reading motivation, narrative texts, and expository texts by gender, following the simulation methods proposed by Muldoon (2019). The results of the study revealed that female participants scored lower on reading strategies and demonstrated poorer performance for narrative and expository texts. There was no gender difference found for reading motivation. These findings will be discussed in relation to our understanding of gender differences in inferential reading comprehension, reading motivation and practical implications for the classroom."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3349"},["text","reading comprehension; reading inference; reading motivation; expository and narrative texts; secondary school"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3350"},["text","Participants The intention was to collect original data from UK Year 7, 8, 9, and 10 mainstream secondary school students. This was through schools and word of mouth. Unfortunately, schools who were approached were not able distribute the study information in time for data collection before the summer break. In total 27 students started the study and completed data was collected from 9 (5 males, 4 females; M age = 13.83 years, SD = 2.45). These data were used to inform a simulated dataset to test the study predictions."]],["elementText",{"elementTextId":"3365"},["text","Materials Reading Motivation To assess students’ reading motivation 7 out of 8 domains from “The Motivation for Reading Questionnaire” (MRQ): A Revised Version (Wang &amp; Guthrie, 2004) were used (grades domain from extrinsic scale was removed). The forty-one-question scale measured extrinsic and intrinsic motivation. Intrinsic motivation consisted of three domains: curiosity (7 items), involvement (7 items), and preference for challenge (5 items). Seven scales (curiosity, involvement, challenge, recognition, social and competition) reported good internal consistency (Cronbach’s alpha ˃ .70; Wang and Guthrie, 2004). An example of intrinsic motivation item: “I enjoy a long, involved story or fiction book”. Extrinsic motivation measured the following four domains: recognition (5 items), social (7 items), competition (6 items), and compliance (4 items). An example of extrinsic motivation item: “I like having my friends sometimes tell me I am a good reader”. Each statement had four possible answers, which were assigned values from 0 to 3 (very different from me = 0, a little different from me = 1, a little like me = 2, a lot like me = 3), and participants were asked to select the most appropriate for them. Scoring for negative item 40 was reversed before assigning the values. Text Genre Participants were asked to read 12 narrative, and 12 expository texts. Narrative texts focussed on human characteristics and activities, based on interactions with different social groups, as families, friends, peers at schools and youth clubs. Expository texts, were science-based, underpinned by chemistry, physics, biology, and geology. Each text consisted of 7 sentences, with 2 critical sentences that required an inference in order to integrate their meanings. The distance between two critical sentences was varied – either adjacent or separated by up to 3 sentences of filler text to minimise the detection of any pattern by readers, which might result in a focus on just the critical sentences, rather than reading the text as a whole. Each text was followed by one question, requiring choosing one answer from yes/no options (correct answer was allocated a value = 1; incorrect answer = 0), which assessed participant’s inference ability and comprehension. Participants completed two practice items, one expository and one narrative text, before starting the test. Reading Strategies Reading strategy knowledge was assessed with items from the Contextualized Reading Strategy Survey (CReSS; Denton et al., 2015). In this, participants read situation-based reading scenarios and rate how frequently they use different reading strategies in those situations. The three selected scenarios assessed reader’s construction integration abilities (Kintsch, 1988). An example of a scenario used for the study “As a homework assignment for your English class, you have been asked to read a story from your textbook. Tomorrow your teacher will give you a quiz about the story. Which of these things do you do to help you understand a story while you are reading or after reading?”. The following strategies were displayed for students to choose from “I try to make mental pictures of the information in the story while I read. While I am reading, I think about how the parts of the story go together. I think about what the characters are doing in the story and why they are acting as they are. I predict what I think will happen next. I think about how this story is like other stories I have read”. Each strategy had four response options, with values assigned from 0 to 3 (I almost never do this = 0; I sometimes do this = 1; I usually do this = 2; I almost always do this = 3) for participants to choose the one, which they use the most."]],["elementText",{"elementTextId":"3366"},["text","Procedure The study was hosted on Qualtrics platform. First, the parents/ guardians accessed the study via a link, then they provided their consent. The child saw the next screen, where they read the information about the study and provided their assent. Participants were asked to complete the task at home in their own time, outside of their school commitment time. Participants were asked to provide information about their gender, age - month and year only. Task order was: (1) reading strategies, (2) narrative texts with yes/no questions about the texts, (3) expository texts with yes/no questions about the texts, and (4) intrinsic and extrinsic reading questionnaire. For the reading strategies questionnaire, participants were asked to read 3 scenarios, as described above. They read each scenario and then indicated on a 4-point Likert scale how frequently they used each strategy. To assess inference making, participants read 12 short narrative texts, and also 12 short expository texts. Each text was shown on 1 screen with the inference-tapping question on a separate screen. They pressed a button next to YES or NO to provide their answer. The final task required participants to complete a reading motivation questionnaire. They read 19 statements for intrinsic and 22 statements for extrinsic reading motivation, and then indicated on the 4-point Likert scale how likely of them it was, as described above. The whole procedure took approximately 30 minutes. Collected data was stored in password-protected file, on password-protected Master student’s Lancaster University’s Office 360, accessed through password-protected laptop."]],["elementText",{"elementTextId":"3367"},["text","Ethical Considerations The research was approved by the University Department Ethics Committee, and conducted in line with the Lancaster University ethics guidelines: https://www.lancaster.ac.uk/sci-tech/research/ethics/, and the BPS Code of Ethics and Conduct (2018). Measures were taken to maintain the participants’ anonymity: identifiable information as participant’s name, school name, participant’s full date of birth were not collected; with references to data collection in England. To investigate the study purposes of age and gender related differences, participant’s month and year of birth were obtained, and the student’s gender as reported by participant were collected."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3351"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3352"},["text","Data/csv."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3353"},["text"," Jumatova2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3354"},["text","Wai Man Ko, Charlotte Graham"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3355"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3356"},["text","N/A"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3357"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3358"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"3359"},["text","LA14YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3360"},["text","Prof. Kate Cain"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3361"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3362"},["text","Cognitive, Developmental"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3363"},["text","9 participants. Data simulation using set.seed(16) function in R Studio was used to create a larger sample and simulate data analysis "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3364"},["text","Regression, other"]]]]]]]],["item",{"itemId":"164","public":"1","featured":"0"},["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3330"},["text","Can better linguistic fluency improve the memorability and credibility of a sentence?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3331"},["text","Hamish Bromley"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3332"},["text","07.09.2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3333"},["text","Processing fluency is often defined as how easy information is to comprehend based on a range of characteristics. One form of processing fluency is linguistic fluency, which refers to how easy a sentence is to interpret, regardless of the information within it. Some research suggests that disfluency can increase the recall of material, but this is contested. Previous studies have also shown that the linguistic fluency of a sentence can be improved with literary devices, such as rhyme, and that this can result in better perceptions of credibility. Research has yet to investigate how alliteration, as an example of linguistic fluency, could improve perceptions of credibility and the memorability of a sentence. This research investigated this by operationalising lists of alliterating and non-alliterating aphorisms, alongside measures of self-reported credibility and memorability, in a between-subjects study. Results of two independent t-tests provided two significant results, suggesting that better linguistic fluency improves the credibility and memorability of a sentence. Implications for researchers, the legal system and advertising are discussed. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3334"},["text","Linguistic Fluency, Alliteration, Advertising,Memory,Credibility"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3335"},["text","Materials \r\nThe preliminary five aphorisms were provided by Astroten with five further aphorisms being added to increase the power of the study. Aphorisms that were selected came from various literary examples, such as quotes from English Literature (Williams, 2011). Alternatively, some aphorisms were created using the definition “a short clever saying that is intended to express a general truth” (Cambridge Dictionary, 2022). The most common alliterating aphorisms, such as “All roads lead to Rome”, were purposefully avoided so that the effect of familiarity had a reduced effect on the memorability self-report. When creating the non-alliterating aphorisms, alliterating words were exchanged for non-alliterating words using a thesaurus so that the change in alliterative properties did not affect the overall meaning. The alliterating and non-alliterating aphorisms were kept divided into two different lists and were counterbalanced in a random order for each participant (Appendix C). Participants were asked to rate the credibility of the aphorisms based on a Likert scale of 1-9, in parallel with the scale used by McGlone and Tofighbakhsh (1999). \r\nParticipants were asked to complete two games of Sudoku as a filler task (Appendix D). The grids were designed so that participants would begin with the easier version and move on to a more challenging version to ensure that the task occupied the full amount of time. Instructions were provided so that those who were unfamiliar with the game were still able to attempt the task. \r\n18 \r\nAdditionally, participants were given a piece of paper with 10 individual sections to write down as many of the aphorisms as they could remember at the end of the study. They were also provided with a pen, and time was kept using a watch. \r\nDesign \r\nThis study used a between-subjects design. This was chosen because there was a strong chance that order effects would impact the results of the memory test in a repeated measures design, due to the similarity between the alliterating and non-alliterating aphorisms. Choosing to mix the aphorisms could have resulted in demand characteristics affecting the results as the disparity between them would have been obvious to the participant. This is something that Oppenheimer and Frank (2008) were also keen to avoid. A quantitative data collection approach was taken because it was judged as the most appropriate way to measure memory, as well as facilitating comparison with other studies that have employed similar methods (McGlone & Tofighbakhsh, 1999; Kara-Yakoubian et al 2022). Participants were either part of the alliterating or non-alliterating aphorisms condition. \r\nProcedure \r\nEthical approval for this study was given by the supervisor of this research, in line with Lancaster University Psychology Department protocols (Appendix E). When participants were approached to take part in the study they were first asked to read an information sheet (Appendix F) followed by a consent form, completion of which evidenced their informed consent to take part. Participation began in a quiet room within the university library. It was ensured that they could spare 20 minutes to take part and that they had turned off their phones before the study began. They began the study by rating each aphorism in \r\n19 \r\ntheir list on a scale of 1-9 based on how credible they thought the aphorism was. The instructions were read to them, but they also had the opportunity to read them if they were unsure (Appendix G). They were then given three minutes to memorise as many of the aphorisms as possible. \r\nFollowing this, participants spent 10 minutes completing the Sudoku, with instructions again read to them and provided on the sheet. Once the 10 minutes were complete the participants were asked to spend five minutes trying to recall as many of the aphorisms from their list as possible by writing them down (Appendix H). They were given one point for every aphorism they could remember correctly. No points were given if the participants could only remember parts of the aphorism. As short-term memory is often described as being 7+/-2 (Miller 1956), memorisation of the entire list would likely have been impossible. Therefore, a prompt was added by reading the participant the first word from each of their aphorisms after three minutes. This aligns more closely with advertising research, which frequently measures prompted recall (Romaniuk, 2006; Charlesworth et al, 2022). On completion, participants were thanked for their participation in the research and given their £5 payment. They were also provided with a debrief sheet (Appendix I) that provided details of resources related to the study and the contact details of the researcher and supervisor. "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3336"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3337"},["text","Excel/xlsx."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3338"},["text","Bromley2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3339"},["text","Coco"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3340"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3341"},["text","Dissertation"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3342"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3343"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"3344"},["text","Marketing"]]]]]]]],["item",{"itemId":"162","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"159"},["src","https://johnntowse.com/LUSTRE/files/original/dc9d7d92448f53c83db20cb8dfc254eb.doc"],["authentication","428a4dfdf0770470e4931c36e34242d3"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3295"},["text","Facts May Care About Your Feelings:  The Effects of Empirical and Anecdotal Evidence in the Perception of Climate Change "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3296"},["text","Constance Jordan-Turner"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3297"},["text","21/09/2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3298"},["text","Although the effects of humanmade climate change become ever more potent, the consensus gap between climate scientists and the public is as wide as ever. It is critical that climate change communication is improved to try and close this gap. There are several strategies that can be implemented, including using anecdotes alongside or instead of empirical evidence to elicit emotions. In this study, 74 members of the public completed a survey.  Participants were randomly assigned to one of four conditions which dictated the type of evidence they received: no evidence, empirical evidence, anecdotal evidence, or both empirical and anecdotal evidence.  Results suggest that, in general, there was no effect of evidence on participants’ perceptions of climate change. This result held even after controlling for worldview and ideology. These findings have implications for the theory of inserting emotion into climate change communication."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3299"},["text","Climate change, communication, perception, emotion, evidence"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3300"},["text","This study gained ethical approval from the Faculty of Science and Technology Research Ethics Committee.\r\nParticipants and design\r\nThere were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. \r\nEvidence Passages\r\nEmpirical Evidence\r\nThe empirical evidence vignette included a statement explaining that human-induced carbon dioxide emissions and global average temperature have synchronously increased since pre-industrial times, accompanied with graphs demonstrating these upward trends.  The vignette also highlighted the scientific consensus that humanmade climate change is occurring and will have adverse consequences. Finally, the vignette explained that these adverse consequences had already begun to materialise.  The increase of extreme weather events was highlighted in a graph that showed the tripling of weather-related disasters between 1980 and 2010.  Finally, the vignette finished with references for the information it contained (see Appendix B).\r\nAnecdotal Evidence\r\nThe anecdotal evidence vignette contained information about Storms Dudley, Eunice and Franklin which all made landfall in Britain in quick succession in 2022. The storms were a weather-related event that some scientists have linked to climate change (Barrett, 2022); Specifically, the vignette included information about the storms’ destructiveness, such as the cost of the damage they caused, and the number of people killed.  The destructiveness of the storms was highlighted with images of damage and flooding in Wells, Otley, and Brentwood, as well as an image from Blackpool demonstrating the height and power of the waves caused by the storms.  The vignette included a stock image of a man standing in a flooded living room and a short passage outlining the experience of a fictitious character named Matt Johnson whose family home had been severely flooded as a result of the storms. The vignette concluded with a statement from climate scientist Robert Klein who argued that the impact of the storm was exacerbated by climate change, which generated “super storm” conditions.  Finally, there was a reference to an article about the storms and their link to climate change (see Appendix C).\r\nMeasures\r\nTable 1 contains an overview of the measures embedded in the questionnaire.  For the full questionnaire, please refer to Appendix D.\r\nDisaster Belief\r\nThe disaster belief measure measured predicted estimates of the frequency of weather-related disasters that will occur in the listed years. Participants were given an approximate frequency for 2019 from the International Disaster Database. The measure consisted of six items: 2030, 2040, 2050, 2060, 2070 and 2080. Participants responded by typing in their estimated number next to the relevant year.\r\nHarm Extent\r\nThe harm extent measure consisted of questions concerning how much harm that participants think climate change will cause themselves, their family, their community, Britain, other countries, and future generations. There were six items, such as ‘How much do you think climate change will harm you?’, and ‘How much do you think climate change will harm people in Britain?’ Responses were rated from (1) ‘not at all’ to (4) ‘a great deal’.\r\nHarm Timing\r\n\tThe harm timing measure consisted of questions concerning when participants thought climate change will cause harm to themselves, their family, their community, Britain, other countries, and future generations. There were only two items, ‘When do you think climate change will begin to harm Britain?’ and ‘When do you think climate change will begin to harm other countries?’. Responses were rated as (1) ‘Never’, (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’ and (6) ‘Right now’.\r\nCO2 Attributions\r\n\tThe CO2 attributions measure measured how much participants think human carbon dioxide emissions contribute to events such as heatwaves, rising sea levels, flooding, and Storms Dudley, Eunice, and Franklin. There were six items, such as ‘CO2 contribution to the observed increase in atmospheric temperature during the last 130 years’, ‘CO2 contribution to the European heat wave in 2022 that killed over 5,000 people’, and ‘CO2 contribution to storms Dudley, Eunice, and Franklin in the UK (2022)’. These responses were gathered using a sliding scale from 0 to 100%.\r\nIntention\r\nThe intention measure consisted of questions asking about participants’ pro-environmental intentions. There were seven items. Examples of items include ‘I will take part in an environmental event (e.g., Earth hour)’, ‘I will give money to a group that aims to protect the environment’, and ‘I will switch to products that are more environmentally friendly’. The response options were simply ‘Yes’ or ‘No’.   \r\nMitigation\r\n\tThe mitigation measure consisted of questions asking about participants’ support for mitigating policies. There were five items. Example items include, ‘Signing an international treaty that requires Britain to cut its carbon dioxide emissions by 90% by 2050’, ‘Adding a surcharge to electrical bills to establish a fund to help make buildings more energy efficient and to teach British citizens how to reduce energy use’, and ‘Providing tax rebates for people who purchase energy-efficient vehicles or solar panels’. Responses were rated from (1) ‘Strongly Oppose’ to (4) ‘Strongly Support’.\r\nCO2 Adjustment\r\n\tThe CO2 adjustment measure measures how much participants think Britain should adjust its CO2 emissions over the next 10 years. There was only one item: ‘How much should Britain adjust CO2 emissions during the next 10 years?’. Responses were rated from (1) ‘Not at all’ to (6) ‘Reduce by 50%’.\r\nFree-Market Support\r\n\tThe free-market support measure consisted of questions asking about participants’ support for the free market. There were five items. Examples items include, ‘An economic system based on free-markets, unrestrained by government interference, automatically works best to meet human needs’ and ‘The preservation of the free-market system is more important than localized environmental concerns’. Two items, ‘Free and unregulated markets pose important threats to sustainable development’ and ‘The free-market system is likely to promote unsustainable consumption’, required reverse coding upon analysis.\r\nTable 1\r\nMeasures embedded within the questionnaire. The first column contains the name of the measures; the second column contains the instructions on how to respond to items in that measure; and the third column describes how answers to the items were coded.   \r\nMeasure Name\tQuestions\tCoded Response\r\nDisaster belief\tPlease provide an estimate of the frequency of weather-related disasters that will occur in each year (6 items).\tParticipants used the keyboard to type in a number for each year.\r\nHarm extent\tThe following items examine your thoughts about the extent of harm that will be caused by climate change (6 items).\t4-point scale: (1) ‘Not at all’; (2) ‘A little’; (3) ‘A moderate amount’; (4) ‘A great deal’.\r\nHarm timing\tThe following items examine your thoughts about when climate change will begin to cause harm (2 items).\t6-point scale: (1) ‘Never’; (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’; (6) ‘Right now’.\r\nCO2 attribution\tFor each of the following questions, please estimate the contribution from human CO2 emissions to cause each event. For example, 0% would mean humans are not at all responsible, whereas 100% would mean that human CO2 emissions are fully responsible\r\n\tParticipants used the mouse to place their response on a sliding scale. The sliding scale contained the numbers, ‘0’, ‘10’, ‘20’, ‘30’, ‘40’, ‘50’, ‘60’, ‘70’, ‘80’, ‘90’, and ‘100’. \r\n\r\n\r\n\r\nPro-environmental intentions\tPlease indicate whether or not you will engage in the following actions (7 items).\t0 = No\r\n1 = Yes\r\nMitigation\tHow much do you support or oppose the following policies (five items).  \t4-point scale; (1) ‘Strongly Oppose’; (2) ‘Oppose’; (3) ‘Support’; (4) ‘Strongly Support’.\r\nCO2 adjustment\tHow much should Britain adjust CO2 emissions during the next 10 years?\t6-point scale; (1) ‘Not at all’; (2) ‘Reduce by 10%’; (3) ‘Reduce by 20%’; (4) ‘Reduce by 30%’; (5) ‘Reduce by 40%’; (6) ‘Reduce by 50%’.\r\nFree-market belief\tPlease indicate how much you agree with each statement (5 items).\t5-point scale: (1) ‘Strongly Disagree’; (2) ‘Disagree’; (3) ‘Neutral’; (4) ‘Agree’; (5) ‘Strongly Agree’.\r\nDemographic questions\tWhat is your age?\tParticipants used the keyboard to type in a number.\r\n\tWhat is your gender?\t1 = Male; 2 = Female; 3 = Non-binary; 4 = Other; 5 = Prefer Not to Say\r\n\r\nProcedure\r\nAll participants completed a questionnaire assessing their belief in and concern about humanmade climate change and their mitigation beliefs.  The questionnaire was administered online using Qualtrics survey software.  Participants responded to the questionnaire by using either the mouse to select answers or the keyboard to type in numbers. \r\nAt the beginning of the questionnaire, all participants received an information sheet about the aim of the study, the lack of risks associated with participating, and how participant information is stored. Participants were asked to indicate their informed consent. For the full participant information sheet and consent form, please refer to Appendix E. After participants gave their consent and continued onto the survey, they were asked their age and gender. They were then presented with evidence according to the condition they were assigned to.  There were four conditions: no evidence, empirical evidence, anecdotal evidence, and both empirical and anecdotal evidence.\r\nAfter they had read one or both evidence passages, participants answered the disaster belief measure. Next, they answered the CO2 attribution measure. Then they answered the harm extent measure and the harm timing measure. After that was the intention measure, and then they answered the mitigation measure. In the final part of the questionnaire, they were asked how much Britain should cut its CO2 emissions over ten years, and then questions on their support for the free market. Participants were then asked demographic questions about their age and gender. Finally, the participants were given a debrief sheet (Appendix F).\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3301"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3302"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3303"},["text","Jordan-Turner2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3304"},["text","Abigail Travis"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3305"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3306"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3307"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3308"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"3309"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3310"},["text","Dr. Mark Hurlstone"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3311"},["text","Masters"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3312"},["text","Cognitive, Perception"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3313"},["text","74"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3314"},["text","ANCOVA"]]]]]]]],["item",{"itemId":"155","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"161"},["src","https://johnntowse.com/LUSTRE/files/original/8154f97af93267514bfb20a6c3f3ef81.doc"],["authentication","d960205f74b85b3da78afddb4fda542d"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3180"},["text","Farmer and Non-Farmer Attitudes towards Alternative Animal Products"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3181"},["text","Chloe Crawshaw"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3182"},["text","23/09/22"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3183"},["text","Farmers’ livelihoods and way of living could be argued to be under threat from the simultaneous rapid rise of plant-based products, development of cultured products, and our growing understanding of the detrimental impact of traditional animal agriculture. Little research has investigated farmers attitudes towards cultured and plant-based products. Furthermore, famers appear to have limited awareness of these animal product alternatives. This study presented 45 omnivorous farmers and 53 omnivorous non-farmers with information about plant-based burgers, cultured burgers, plant-based milk, and cultured milk. Product acceptance and COM-B facilitators and barriers were explored. Farmers were less accepting of all alternative products than non-farmers, suggesting that their vested interest in the continuation of traditional animal agriculture affected their attitudes towards alternative products. Closer inspection of farmer acceptance suggests that personal investment in animal agriculture also led to differences within farmers, with occupational farmers being less accepting of the products than the members of farming families. The findings are interpreted using the Transtheoretical Model to suggest that regarding the adoption of alternative products, occupational farmers appear to be in the rejection stage, whereas members of farming families appear to be in the contemplation stage. As occupational farmers had more negative attitudes towards the alternative products, they appear more likely to consider the alternatives a threat to their livelihood."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3184"},["text","farmers, plant-based alternatives, cultured products, COM-B Model, Transtheoretical Model"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3185"},["text","Participant Recruitment and Exclusions\r\nParticipant recruitment followed a pre-registered plan (https://aspredicted.org/blind.php?x=QL3_H96). Between July and August 2022 two groups of participants were recruited: adults with experience of livestock farming (Farmers), and a comparison group of adults without experience of livestock farming (Non-Farmers). Farmers make up a very small percentage (0.2%) of the UK population (DEFA, 2021) so we included current farmers, retired farmers, farm workers, and members of farming families.  \r\nFifty-five livestock farmers predominately living in Gloucestershire were recruited using snowball sampling. Farmers that were known to the author were first contacted via telephone, social media, or visited in-person. Interested participants were provided with the URL link to the questionnaire, a brief description of the study, and a request to forward the information to other individuals in the farming community. Individuals without internet access received a paper copy of the questionnaire. \r\nSixty-one non-farmers were recruited through snowball sampling in the same method as for farmers. As farmers are typically older males (DEFRA, 2019), we attempted to match the ages of the non farmers to the farmers and effort was taken to recruit female farmers and members of farming families. Our recruitment plan was to recruit a minimum of 40 participants per group. To qualify for the study, farmers and non-farmers had to be omnivores. \r\nA further 23 farmers and 10 non-farmers were recruited using Prolific by pre-screening for those in the ‘Agriculture, Food, and Natural Resources’ employment sector, the description of the study also encouraged participation among those with “experience of working with farmed animals.” \r\nA total of 130 participants consented to participate: 55 farmers, 61 non-farmers, and a further fourteen who were excluded as they did not reach the demographics section so could not be classified into a group. Following our preregistered exclusion criteria, 18 participants who reported dietary restrictions were excluded (10 Farmers and 8 Non-Farmers). The final sample consisted of 45 Farmers and 53 Non-Farmers. \r\nDesign and Procedure \r\nA 2x4 mixed design was used, with Group as a between-subjects factor with two levels: Farmer and Non-Farmer, and Product type as a within-subjects factors with four levels: plant-based burgers, cultured beef burgers, plant-based milk, and cultured cow’s milk. Participants completed an online questionnaire on Qualtrics (Qualtrics, 2005) that “drew attention to existing and emerging food innovations and explored beliefs and attitudes towards these products “, see Appendix A. The questionnaire took approximately 15 minutes. \r\nEthical Statement \r\nThe study was approved by Lancaster University’s Department of Psychological Ethics Committee. Participation was anonymous and Farmers were not asked to disclose the name or location of their farm. All participants gave their informed consent before accessing the questionnaire. On completion of the questionnaire, participants were debriefed, reminded of their right to withdraw their data, and were thanked.\r\nMaterials\r\n\tThe questionnaire comprised of six sections: vignettes, product acceptance, facilitators and barriers to product acceptance, consumer behaviour, demographics, and farming information.  \r\nVignettes\r\nParticipants were presented with a brief description of factory farming, including its prevalence in the UK and the negative consequence on farmed animals and the environment. See Appendix B for full vignette details and references. Factory farming was chosen as it is the main method of farming in the UK (FAIRR, 2016). Participants were then presented with brief descriptions of plant-based products and methods of creating cultured animal products. Product features were compared against traditional animal products, including the sensory qualities, nutritional content, animal involvement, and environmental impact. Using a similar table to Van Loo et al. (2020), participants were presented with a comparison of the relative environmental impact of a plant-based soya burger and a cultured beef burger compared to a factory farmed beef burger"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3186"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3187"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3188"},["text","Crawshaw2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3189"},["text","HanYi Wang\r\nAmie Suthers"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3190"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3191"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3192"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3193"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"3194"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3210"},["text","Dr Jared Piazza"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3211"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3212"},["text","Social"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3213"},["text","98(45 Farmers and 53 Non-Farmers)"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3214"},["text","Chi-squared\r\nCorrelation\r\nKruskall-Wallis, MANOVA, Wilcoxon Signed Rank, Mann-Whitney U "]]]]]]]],["item",{"itemId":"150","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"153"},["src","https://johnntowse.com/LUSTRE/files/original/2a6af9e3bd67966c26821868b9693304.pdf"],["authentication","7822a912e947086abb3415b7484d575b"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3102"},["text","Facts May Care About Your Feelings:  The Effects of Empirical and Anecdotal Evidence in the Perception of Climate Change "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3103"},["text","Constance Jordan-Turner"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3104"},["text","21/09/2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3105"},["text","Although the effects of humanmade climate change become ever more potent, the consensus gap between climate scientists and the public is as wide as ever. It is critical that climate change communication is improved to try and close this gap. There are several strategies that can be implemented, including using anecdotes alongside or instead of empirical evidence to elicit emotions. In this study, 74 members of the public completed a survey.  Participants were randomly assigned to one of four conditions which dictated the type of evidence they received: no evidence, empirical evidence, anecdotal evidence, or both empirical and anecdotal evidence.  Results suggest that, in general, there was no effect of evidence on participants’ perceptions of climate change. This result held even after controlling for worldview and ideology. These findings have implications for the theory of inserting emotion into climate change communication."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3106"},["text","Climate change, communication, perception, emotion, evidence"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3107"},["text","Participants and design\r\nThere were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. \r\n\r\nThis study gained ethical approval from the Faculty of Science and Technology Research Ethics Committee.\r\nParticipants and design\r\nThere were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. \r\nEvidence Passages\r\nEmpirical Evidence\r\nThe empirical evidence vignette included a statement explaining that human-induced carbon dioxide emissions and global average temperature have synchronously increased since pre-industrial times, accompanied with graphs demonstrating these upward trends.  The vignette also highlighted the scientific consensus that humanmade climate change is occurring and will have adverse consequences. Finally, the vignette explained that these adverse consequences had already begun to materialise.  The increase of extreme weather events was highlighted in a graph that showed the tripling of weather-related disasters between 1980 and 2010.  Finally, the vignette finished with references for the information it contained (see Appendix B).\r\nAnecdotal Evidence\r\nThe anecdotal evidence vignette contained information about Storms Dudley, Eunice and Franklin which all made landfall in Britain in quick succession in 2022. The storms were a weather-related event that some scientists have linked to climate change (Barrett, 2022); Specifically, the vignette included information about the storms’ destructiveness, such as the cost of the damage they caused, and the number of people killed.  The destructiveness of the storms was highlighted with images of damage and flooding in Wells, Otley, and Brentwood, as well as an image from Blackpool demonstrating the height and power of the waves caused by the storms.  The vignette included a stock image of a man standing in a flooded living room and a short passage outlining the experience of a fictitious character named Matt Johnson whose family home had been severely flooded as a result of the storms. The vignette concluded with a statement from climate scientist Robert Klein who argued that the impact of the storm was exacerbated by climate change, which generated “super storm” conditions.  Finally, there was a reference to an article about the storms and their link to climate change (see Appendix C).\r\nMeasures\r\nTable 1 contains an overview of the measures embedded in the questionnaire.  For the full questionnaire, please refer to Appendix D.\r\nDisaster Belief\r\nThe disaster belief measure measured predicted estimates of the frequency of weather-related disasters that will occur in the listed years. Participants were given an approximate frequency for 2019 from the International Disaster Database. The measure consisted of six items: 2030, 2040, 2050, 2060, 2070 and 2080. Participants responded by typing in their estimated number next to the relevant year.\r\nHarm Extent\r\nThe harm extent measure consisted of questions concerning how much harm that participants think climate change will cause themselves, their family, their community, Britain, other countries, and future generations. There were six items, such as ‘How much do you think climate change will harm you?’, and ‘How much do you think climate change will harm people in Britain?’ Responses were rated from (1) ‘not at all’ to (4) ‘a great deal’.\r\nHarm Timing\r\n\tThe harm timing measure consisted of questions concerning when participants thought climate change will cause harm to themselves, their family, their community, Britain, other countries, and future generations. There were only two items, ‘When do you think climate change will begin to harm Britain?’ and ‘When do you think climate change will begin to harm other countries?’. Responses were rated as (1) ‘Never’, (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’ and (6) ‘Right now’.\r\nCO2 Attributions\r\n\tThe CO2 attributions measure measured how much participants think human carbon dioxide emissions contribute to events such as heatwaves, rising sea levels, flooding, and Storms Dudley, Eunice, and Franklin. There were six items, such as ‘CO2 contribution to the observed increase in atmospheric temperature during the last 130 years’, ‘CO2 contribution to the European heat wave in 2022 that killed over 5,000 people’, and ‘CO2 contribution to storms Dudley, Eunice, and Franklin in the UK (2022)’. These responses were gathered using a sliding scale from 0 to 100%.\r\nIntention\r\nThe intention measure consisted of questions asking about participants’ pro-environmental intentions. There were seven items. Examples of items include ‘I will take part in an environmental event (e.g., Earth hour)’, ‘I will give money to a group that aims to protect the environment’, and ‘I will switch to products that are more environmentally friendly’. The response options were simply ‘Yes’ or ‘No’.   \r\nMitigation\r\n\tThe mitigation measure consisted of questions asking about participants’ support for mitigating policies. There were five items. Example items include, ‘Signing an international treaty that requires Britain to cut its carbon dioxide emissions by 90% by 2050’, ‘Adding a surcharge to electrical bills to establish a fund to help make buildings more energy efficient and to teach British citizens how to reduce energy use’, and ‘Providing tax rebates for people who purchase energy-efficient vehicles or solar panels’. Responses were rated from (1) ‘Strongly Oppose’ to (4) ‘Strongly Support’.\r\nCO2 Adjustment\r\n\tThe CO2 adjustment measure measures how much participants think Britain should adjust its CO2 emissions over the next 10 years. There was only one item: ‘How much should Britain adjust CO2 emissions during the next 10 years?’. Responses were rated from (1) ‘Not at all’ to (6) ‘Reduce by 50%’.\r\nFree-Market Support\r\n\tThe free-market support measure consisted of questions asking about participants’ support for the free market. There were five items. Examples items include, ‘An economic system based on free-markets, unrestrained by government interference, automatically works best to meet human needs’ and ‘The preservation of the free-market system is more important than localized environmental concerns’. Two items, ‘Free and unregulated markets pose important threats to sustainable development’ and ‘The free-market system is likely to promote unsustainable consumption’, required reverse coding upon analysis.\r\nTable 1\r\nMeasures embedded within the questionnaire. The first column contains the name of the measures; the second column contains the instructions on how to respond to items in that measure; and the third column describes how answers to the items were coded.   \r\nMeasure Name\tQuestions\tCoded Response\r\nDisaster belief\tPlease provide an estimate of the frequency of weather-related disasters that will occur in each year (6 items).\tParticipants used the keyboard to type in a number for each year.\r\nHarm extent\tThe following items examine your thoughts about the extent of harm that will be caused by climate change (6 items).\t4-point scale: (1) ‘Not at all’; (2) ‘A little’; (3) ‘A moderate amount’; (4) ‘A great deal’.\r\nHarm timing\tThe following items examine your thoughts about when climate change will begin to cause harm (2 items).\t6-point scale: (1) ‘Never’; (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’; (6) ‘Right now’.\r\nCO2 attribution\tFor each of the following questions, please estimate the contribution from human CO2 emissions to cause each event. For example, 0% would mean humans are not at all responsible, whereas 100% would mean that human CO2 emissions are fully responsible\r\n\tParticipants used the mouse to place their response on a sliding scale. The sliding scale contained the numbers, ‘0’, ‘10’, ‘20’, ‘30’, ‘40’, ‘50’, ‘60’, ‘70’, ‘80’, ‘90’, and ‘100’. \r\n\r\n\r\n\r\nPro-environmental intentions\tPlease indicate whether or not you will engage in the following actions (7 items).\t0 = No\r\n1 = Yes\r\nMitigation\tHow much do you support or oppose the following policies (five items).  \t4-point scale; (1) ‘Strongly Oppose’; (2) ‘Oppose’; (3) ‘Support’; (4) ‘Strongly Support’.\r\nCO2 adjustment\tHow much should Britain adjust CO2 emissions during the next 10 years?\t6-point scale; (1) ‘Not at all’; (2) ‘Reduce by 10%’; (3) ‘Reduce by 20%’; (4) ‘Reduce by 30%’; (5) ‘Reduce by 40%’; (6) ‘Reduce by 50%’.\r\nFree-market belief\tPlease indicate how much you agree with each statement (5 items).\t5-point scale: (1) ‘Strongly Disagree’; (2) ‘Disagree’; (3) ‘Neutral’; (4) ‘Agree’; (5) ‘Strongly Agree’.\r\nDemographic questions\tWhat is your age?\tParticipants used the keyboard to type in a number.\r\n\tWhat is your gender?\t1 = Male; 2 = Female; 3 = Non-binary; 4 = Other; 5 = Prefer Not to Say\r\n\r\nProcedure\r\nAll participants completed a questionnaire assessing their belief in and concern about humanmade climate change and their mitigation beliefs.  The questionnaire was administered online using Qualtrics survey software.  Participants responded to the questionnaire by using either the mouse to select answers or the keyboard to type in numbers. \r\nAt the beginning of the questionnaire, all participants received an information sheet about the aim of the study, the lack of risks associated with participating, and how participant information is stored. Participants were asked to indicate their informed consent. For the full participant information sheet and consent form, please refer to Appendix E. After participants gave their consent and continued onto the survey, they were asked their age and gender. They were then presented with evidence according to the condition they were assigned to.  There were four conditions: no evidence, empirical evidence, anecdotal evidence, and both empirical and anecdotal evidence.\r\nAfter they had read one or both evidence passages, participants answered the disaster belief measure. Next, they answered the CO2 attribution measure. Then they answered the harm extent measure and the harm timing measure. After that was the intention measure, and then they answered the mitigation measure. In the final part of the questionnaire, they were asked how much Britain should cut its CO2 emissions over ten years, and then questions on their support for the free market. Participants were then asked demographic questions about their age and gender. Finally, the participants were given a debrief sheet (Appendix F)."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3108"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3109"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3110"},["text","Jordan-Turner2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3111"},["text","Sacha Crossley"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3112"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3113"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3114"},["text","Data"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3129"},["text","Dr. Mark Hurlstone"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3130"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3131"},["text","Cognitive, Perception"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3132"},["text","74"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3133"},["text","ANCOVA"]]]]]]]],["item",{"itemId":"147","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"137"},["src","https://johnntowse.com/LUSTRE/files/original/f32d9fb1ed51218774543381b3025654.xlsx"],["authentication","9d383cde2bea34174cef2f6b085935ca"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3042"},["text","                             Do inward and outward consonants and vowels\r\nhave different effects on customer’s liking rates\r\ntowards the brand names?\r\n"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3043"},["text","Keung Wang Shan"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3044"},["text","5/9/2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3045"},["text","The origin of speech development starts with the way that infants or children produce their first words. In the early stage of speech acquisition, children tend to produce particular syllables that are low in energy to produce, such as intrasyllabic and intersyllabic consonant-vowel co-occurrence patterns (MacNeilage et al., 2000). Such patterns may have an effect on individual’s preference for words later in life, such as for brand names. More pointedly, according to Topolinski et al. (2014), there is an in-out effect which significantly affect individual’s liking rates towards the brand names that contain inward and outward consonants. However, previous findings have only focused on such effects on consonants, whereas there is insufficient research on the combination effects of consonants and vowels on brand names. Therefore, this study is designed to investigate whether such in-out effects of both consonants and vowels of English brand names have association with customer’s emotional response to the words, as well as whether the involvement of MacNeilage syllables in the brand names are associated with customer’s liking rate. The whole experiment was conducted through an online questionnaire consisting of 360 sound stimuli to test on participant’s liking rate towards the brand names which are non-words with the combination of inward and outward consonants and vowels, and Macneilage syllables. Results of the study showed that liking rates towards the brand names are significantly increased for the ones that include inward consonants and vowels, while lower liking rates were associated with outward consonants and vowels. Not to mention, no significant relationship was found between the number of MacNeilage syllables and one’s preference towards the brand names, yet individuals had higher preference for brand names that contained MacNeilage syllables as the first syllable of the word. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3046"},["text","Consonants, vowels, MacNeilage syllables, brand names, liking rates"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3047"},["text","Participants\r\nA total of 51 participants who spoke different first languages were recruited through researcher’s family and friends as well as invited via SONA. They were all healthy individuals with normal vision and hearing, all aged 18 or above with no health conditions. The participants included 23 males and 28 females, with the age range from 22 to 28 and a mean age of 23.33, SD=.\r\nMaterials\r\nThe study was carried out as an online questionnaire which consisted of four open ended questions at the beginning and 360 questions with a 10-point Likert scale to display the answers. The whole questionnaire was based on the liking rate of the brand names that were presented as sound stimuli displayed in the questionnaire. The first four open ended questions were designed to ask participants’ age, gender, first language and whether they speak other languages (see Appendix D). Next, 360 questions each containing an audio of a sound stimulus that was between one to three seconds were presented in the questionnaire (see Appendix D). All sound stimuli were recorded by the researcher’s supervisor who was a native English speaker with a Northern English accent with training in phonology beforehand, which were also produced in a monotone. Within the 360 sound stimuli, they were divided into six different sets which included six combinations of inward and outward consonants and vowels. The total six sets of stimuli included nonwords that contained consonants that required the articulation from front to the middle to back of the mouth (inward) (FMB), from front to back to middle (FBM), from middle to front to back (MFB), from middle to back to front (MBF), from back to middle to front (outward) (BMF) and from back to front to middle (BFM). There was a total of 60 stimuli with the same articulation of consonants and different articulation of vowels in each set, and 10 stimuli with the same articulation of both consonants and vowels in each set. Within each set of the same articulation of consonants, six possible combinations of front/middle/back vowels were paired up with the consonants to create the stimuli so that every possible arrangement of front/middle/back consonants and vowels was tested in the questionnaire. Moreover, among the 360 stimuli, 120 of them contained zero MacNeilage syllables, 178 of them contained one MacNeilage syllables while 62 of them contained three MacNeilage syllables. To ensure that there was no personal bias towards the brand names, all stimuli were nonwords that were created by the researcher so that participants would not be familiar with any of the brand names.\r\nProcedure\r\nBefore the study began, all participants were sent a participant information sheet and consent form through email (see Appendix A & B). Participants were then also given a link to the online questionnaire which was attached in the same email. At the beginning of the questionnaire, four open-ended questions on personal information were presented and participants were asked to answer their age, gender, first language and whether they speak other languages (see Appendix D). After completing the four questions, participants had to answer 360 questions with each containing an audio of a sound stimuli, which were referred as brand names in this survey. Each question was displayed as ‘how much do you like this brand name’ and participants were asked to rate each sound stimuli according to their preference on the 10-point Likert scale, labelled as 1 as the lowest and 10 as the highest (see Appendix D). There was a ‘play’ button in every question where participants could play the sound stimulus and they were allowed to play the audio as many times as they prefer if they wished. In the questionnaire, five questions were presented on each page and there was 73 pages in total, including one page in the beginning for the four open-ended questions. The 360 questions on the sound stimuli were presented in randomised order for each participant to ensure there were no order effects relating to individual stimuli in the data. The whole study took around 20 to 30 minutes depending on whether the participants replayed the audios or not. After completing the questionnaire, all participants were delivered a debrief sheet via email, allowing them to ask any questions regarding the study (see Appendix C).\r\nEthics\r\nThe study was granted ethics approval on 19/05/2022. Both a participants information sheet and consent form were delivered to all participants before the study began to indicate their rights to withdraw up to three weeks after participating in the experiment if they had changed their minds. After completion of the questionnaire, a debrief sheet was sent out to participants to allow them to raise questions regarding the study. They were also informed that their participation was confidential, with all data stored in encrypted files.\r\n\r\n\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3048"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3049"},["text","Data/Excel.csv\r\nData/R.r"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3050"},["text","none"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3051"},["text","Keung Wang Shan"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3052"},["text","open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3053"},["text","none"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3054"},["text","english"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3055"},["text","data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"3056"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3057"},["text","Padraic Moonaghan"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3058"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3059"},["text","Developmental Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3060"},["text","51 participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3061"},["text","Linear mixed effects modelling"]]]]]]]],["item",{"itemId":"143","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"135"},["src","https://johnntowse.com/LUSTRE/files/original/168c73959ed52a18ad7005f6a70fa065.csv"],["authentication","d70674b2d31093cc490b1257b76ace7e"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2961"},["text","Do trustworthiness judgements help people to recognise synthetic faces?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2962"},["text","Haisa Shan"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2963"},["text","8 September 2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2964"},["text","Recent advances in digital image generative models have allowed for artificial creation of fake imagery such as synthesising highly photorealistic human faces. Style-based Generative Adversarial Networks (StyleGAN) is one of the most state-of-the-art generative models in this field, and has been widely used on facial image generation. However, with the increasing ease of using such image generative models, the security in many domains, such as forensic, border control and mass media, is vulnerable in front of the potential threats resulted from the misuse of image generative technologies. To date there has only been limited empirical research into the facial characteristics of StyleGAN-generated faces to support the design of detection methods against such synthetic faces. This study used StyleGAN2 (an improved version of StyleGAN) to generate faces and invited people to complete two facial image evaluation tasks, 1) Discrimination task, 2) Trustworthiness rating task. The study results demonstrated that, in the discrimination task, subjects had trouble recognising synthetic faces by direct/explicit judgement; while in the trustworthiness rating task, subjects perceived the synthetic faces as significantly more trustworthy than real faces. The study further analysed gender bias and ethnicity bias on the perception of facial trustworthiness, with results showing some differences between different levels of gender and ethnicity. In conclusion, people’s ability to recognise synthetic faces is poor, but it is possible that people rely on the perception of facial trustworthiness to discriminate synthetic from real faces. The findings in this study have implications for the development of detection methods against digitally generated faces."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2965"},["text","StyleGAN, synthetic face, trustworthiness perception, facial trustworthiness"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2966"},["text","Subjects and design\r\nThree hundred and fifty-seven subjects (114 males, mean age = 25.2, SD = 5.8; 227 females, mean age = 25.0, SD = 6.3; 10 non-binary, mean age = 23.6, SD = 8.93) were recruited to complete an online survey test delivered on www.qualtrics.com. The responses of subjects who started but did not complete the online survey were eliminated to avoid distorting the research results. We used computer-synthesised facial images in this research as fake faces, mixed with real faces to examine people’s ability to detect fake faces and perceptual differences of trustworthiness between real/fake faces. Subjects did not get rewards for their participation, though they could see the test score of their performances at the end of the survey. The Qualtrics survey was based on a within-subjects design in which all subjects viewed the same two sets of adult facial images and completed each of the two tasks. To eliminate the effect of between-sets difference, the use of each image sets was counterbalanced in the individual test for each subject. Before the survey started, all subjects provided informed consent and completed a demographic questionnaire about their age, gender, ethnicity. In terms of the experimental power of 0.8 and significance level of 0.05, with a small effect, the power calculation indicated that the study needed at least 198 subjects.\r\nStimuli\r\nA total of thirty-two human facial images (1024×1024 resolution), including 16 real and 16 synthetic faces, were used as stimuli in the survey. All real faces were taken from a publicly available dataset for high-quality human facial images, Flickr-Faces-HQ (FFHQ), which is created as a benchmark for GAN (see https://github.com/NVlabs/ffhq-dataset), and all synthetic faces were gained from the dataset of the generative image modeling, StyleGAN2 (see https://github.com/NVlabs/stylegan2). To ensure a diverse dataset, in each of the two sets of faces, there were 4 Black, 4 East Asian, 4 South Asian, 4 White, and 2 males and 2 females for each ethnicity. Among the sixteen faces of each set, half of them were real and half were synthetic, but this was unknown to subjects.\r\nProcedure\r\nFirst, subjects completed a short questionnaire for demographic information (age, gender, ethnicity), and subjects had to be 18 years of age or older to take part. Prior to the main body of test, there was an example of real and synthetic faces presented to provide subjects with a general impression of what real and synthetic faces look like. Subjects then were asked to complete two face evaluating tasks, 1) Discrimination Task, 2) Trustworthiness Rating Task. The two tasks were presented to subjects in a counterbalanced order to check for any possible order effects. Before the start of each task, participants were informed that they would see a series of 16 facial images, and that they had to carry out their evaluation following the instructions provided. In both tasks, only one image was presented at a time and individual images appeared in a random order.\r\nIn the discrimination task, participants made their decision between two choices, “real” or “synthetic”, to classify the 16 faces according to whether they thought the presented faces were real or not. Subjects did not receive immediate feedback during the task on the correctness of their classifications. In this task, subjects relied on direct/explicit judgments. In the trustworthiness rating task, subjects were required to rate how trustworthy they thought each of 16 faces looked using a 7-point Likert scale (1 = extremely untrustworthy; 4 = neither untrustworthy nor trustworthy; 7 = extremely trustworthy). We instructed subjects that they did not need to consider face authenticity in this task, and they could just assume that the faces shown to them were all of real people. Although there was no time limit to respond for trustworthiness rating, we encouraged subjects to rely on their intuitions and provide their responses to work as quickly as possible. In this task, we expected to trigger a relatively indirect/implicit approach to evaluate faces as compared to direct/explicit judgement on face authenticity, specifically by trustworthiness perception. At the end of the survey, subjects saw a result report of their own mean trustworthiness rating scores for real and synthetic faces, and their mean accuracy in classifying real and synthetic faces in the discrimination task."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2967"},["text","Haisa Shan"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2968"},["text","data/Excel.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2969"},["text","None"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2970"},["text","Haisa Shan"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2971"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2972"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2973"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2974"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2975"},["text","None"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2976"},["text","Sophie Nightingale"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2977"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2978"},["text","Cognitive, Perception; Forensic; Social"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2979"},["text","357 Participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2980"},["text","ANOVA; Power Analysis; T-Test"]]]]]]]],["item",{"itemId":"139","public":"1","featured":"0"},["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2908"},["text","The impact of retribution on perception of transgressor by others "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2909"},["text","Olivia Wilson "]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2910"},["text","2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2911"},["text","Emotions play a key role in within society, behaviour and human life with moral emotions such as guilt, regret and shame being able to influence individuals’ judgments and actions. For example, a person who experiences guilt will want to fix their wrongdoing that has caused this. There are times where these efforts to repair ones transgression, can lead an individual to self-punish in order to repair bonds with others and reduce negative consequences of the situation. The present study experimentally investigated the effect of self-punishment intensity on perceptions of a transgressor. Participants were randomly assigned to one of three conditions of self-punishment intensity (low, correct and high). Vignettes were manipulated for each condition and presented for participants to read for them to answer questions on their judgments of the transgressor (perceptions of guilt, shame, regret, moral character, and trustworthiness, their willingness to forgive the transgressor, how likely they thought they would reoffend in the future) and rated this on a Likert scale of 0-5. Participants allocated to low self-punishment had more negative perceptions towards the transgressor overall when compared to correct self-punishment. However, this was not found beyond this as no differences were seen for those within the high self-punishment condition "]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2912"},["text","Participants. Participants were recruited through the use of LU Sona system as well as opportunity sampling through use of social media and network platforms accessible. A total of 174 responses were collected via Qualtrics, of those 158 have been successfully completed through to the end whilst 16 have only been started and answered few questions at most. Therefore, the decision has been made to exclude any incomplete attempts. This resulted in a final sample of 158 of which 54 are in the high punishment condition, 52 in low punishment condition and 52 in correct punishment. \r\nDesign. This is a one-factor study with 3 levels (self-punishment: Low punishment, correct punishment, and high punishment) between-subjects design. Qualtrics randomly allocated participants to one of the three conditions. \r\nMaterials. A short hypothetical vignette was used to describe an event between two individuals; ‘Simon’ the transgressor and his friend, who he steals money from. With each of the punishment conditions, the vignette introduced the scenario with the same starting sentences to create the scene of someone performing a transgression against their friend with feelings of self-directed negative affect presented by the transgressor: \r\nSimon is out with his friends when he noticed that a member of his group has left their wallet unattended. Simon helps himself to the £40 that was in the wallet. His friend eventually realises that the money has been stolen and seems distressed. The next day, Simon feels bad for his actions and confesses to his friend that he took the money. \r\nThe final sentence of the vignettes was manipulated for each of the three conditions. The sentence stated the amount of money returned to Simon’s friend, which was either less than originally taken (low punishment, £20), same amount (correct punishment, £40) or more than originally taken (high punishment, £60). \r\nHe gives his friend all the money he has in his wallet, which came to £20 (or £40, or \r\n£60). \r\nHypothetical vignettes have been a popular method to explore social actions within research allowing actions to be explored in context to specific situations, people’s judgments, reactions and perceptions of the scenario being described and/or the individual people within the vignette. It allows this all to be clarified in the form of data collection and provides a less personal, and therefore less threatening way of exploring sensitive issues and topics in society (Barter & Renold, 1999; Hughs, 1998; Schoenberg & Ravdal, 2000). Vignettes are a valuable technique for exploring perceptions of situations and have been utilised previously in research on guilt and perceptions of a transgressor post-transgression (McLatchie, 2019; Manstead & Semin, 1981; Dijk, de Jong & Peters, 2009) and so have been utilised in this research of intensity of self-punishment post-transgression. \r\nEmpirical research has shown that emotions and perceptions of guilt specifically focuses attention on the behaviour and action that has occurred which has in turn elicited these feelings (Tangney & Dearing, 2002). This is why the vignette in the present study was written with a particular emphasis on presenting the transgressor to be feeling remorse/guilt after failing to adhere to a social standard, being explicitly stated through acceptance of responsibility. This was done through stating that Simon ‘felt bad for his actions’, intentionally presenting to participants that, regardless of the punishment, Simon did know his behaviour was wrong. It can also be seen in this study through the motivations and efforts to recompensate the wrongdoing through his self-punishment and returning of a quantity of money. Absence of this could imply to participants a lack of emotional response, this could have impacted judgments on Simon regardless of the presence of punishment or not. \r\nAs stated previously, other emotions can be used synonymously within conversation when referring to guilt, such as self-conscious emotions like regret and shame; it was important to ensure that guilt was specifically being portrayed. McLatchie (2019) ensured this in his study investigating punishment types (no punishment, self-punishment, and other punishment). McLatchie used a vignette that described interpersonal violations as these are primarily associated with guilt than the other emotions. This is because it includes other individuals and not merely directed at the self where the common emotion that would most likely be triggered would be shame instead. Due to this, the present study also used a vignette that described an interpersonal violation of moral and social standards with the last sentence manipulated to present three self-punishment conditions based on varying intensities. These terms are popularly used interchangeably within conversation due to multiple similarities between them (Shen, 2018; Bhushan, Basu & Dutta; 2020; Stearns & Parrott, 2012), \r\nParticipants were then asked a series of questions which gathered information on the participants judgments of Simon. Participants were asked to rate the extent of the perceived guilt, shame, and regret of the transgressor as a third-party observer which keeps in line with current research which provides evidence for a strong internal consistency of these measures (McLatchie, 2019). It is also consistent with previous research where the same elements were combined to calculate an overall guilt score. This emphasised the importance of these emotional responses and behaviours that an individual may present when judging overall guilt being experienced by the perpetrator. How much the participant thinks Simon (the transgressor) deserves to be forgiven was also measured. This was done with an adapted version of Zhu et al.’s (2017) way of measuring this and has proved to be effective in prior research related to guilt and self-punishment (McLatchie, 2019). The final questions were – how likely the participants thought Simon would reoffend, and to what extent they thought the punishment performed was sufficient for the transgression committed. All answers were presented and rated on a Likert scale with the question above. \r\nProcedure. Participants were invited to partake in a study aiming to evaluate a ‘social action’. Qualtrics was used to provide the survey to participants where they were asked to read through the vignette prior to moving through the questions and answers which measured their responses. As each question appeared, the vignette remaining at the top of the screen for reference throughout. Answers were presented on a 6-point Likert scale ranging from 0 (“Not at all”) to 5 (“Completely”) which they were required to choose their response through a rating. \r\nOnce participants completed this survey, a final section asked participants to provide demographic information with a full debrief. Demographic information included basic information such as the participants age and gender. Additional questions were included in order to gain an insight into the participants experience with situations such as the one described in the vignette and their personal experiences with guilt allowing any influences of the participants character to be seen when analysing results. These include being asked if they have ever had an experience as the protagonist (Simon in this case), someone who has been stolen from, and if they are prone to feelings of guilt. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2913"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2914"},["text","Data R AStudio .csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2915"},["text","Wilson2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2916"},["text","Anastasija Jumatova"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2917"},["text","Open (unless stated otherwise)"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2918"},["text","None (unless stated otherwise)"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2919"},["text","English "]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2920"},["text","Data and Text "]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2921"},["text","Tamara Rakic"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2922"},["text","Masters"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2923"},["text","Social "]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2924"},["text","158 participants ( 54 are in the high punishment condition, 52 in low punishment condition and 52 in correct punishment)."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2925"},["text","Quantitative "]]]]]]]],["item",{"itemId":"137","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"131"},["src","https://johnntowse.com/LUSTRE/files/original/479c9a1888cc1f0fda97893b220919cd.doc"],["authentication","666af35ed0df5544aff385f320bf5c81"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2869"},["text","Exporing the Effect of Visual Complexity on Recall"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2870"},["text","Hayleigh Proctor "]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2871"},["text","08/09/2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2872"},["text","This study was conducted to explore the effect of visual complexity on an individuals` recall of product brands and their attributes in either simple or complex adverts . Within the field of visual complexity, there has been contradiction as to whether complexity helps or hinders recall, this study aims to resolve this question. A survey was conducted to measure their free and cued recall for adverts that varied in their visual complexity. The complex advertisements were defined as having three objects included whilst the simple advertisements had only one object included. This was decided to align with the industry standard for defining visual complexity as set by Attneave (1954), Snodgrass & Vanderwart (1980) and Chikhman et al., (2012). A percentage scoring system was used to compare overall memory performance. The data showed that those in the simple condition performed better compared to those in the complex condition. However, this was not the case for every individual. The results found the effects of complexity to be marginally significant (p < 0.09); however, the study had limited power, and a replication with a larger population could provide a more complete picture of the influence of the independent variable. Whilst this study does not provide a definitive conclusion towards the effect of visual complexity, it does explore and provide an insight into the effects of complexity on recall of product attributes in advertisements. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2873"},["text","#visualcomplexity #recall #free-recall #cued-recall #advertisements #simple #complex"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2874"},["text","PARTICIPANTS \r\nThe larger the number of participants in a study, the better-protected results will be from extraneous variables. For this reason, the participants were collected through random snowball sampling (Emerson, 2015). Each condition had 22 participants, a minimum age of 16 being the only participation condition. The participants were randomly allocated to each one of the four experimental conditions, providing 88 total participants (N= 88). There were no gender requirements for participation (Females (N = 47), Males (N = 31), Other (N = 4)). \r\nThe majority of participants were born in the U.K. (N = 46) or Poland (N = 35). The majority are currently residing in England (N = 57) or Poland (N = 21), but responses were still collected from further afield, such as France and the U.S.A. (N = 10). The majority of participants fell into the two youngest age categories, 16 to 18-year-olds (N = 22) and 22 to 27-year-olds (N = 37). \r\nGeneral demographic information provided insight into the advertisement exposure in participants' generic routines. The majority of participants were native English speakers (N = 49). The majority of participants use streaming services (N = 76), of which just under half of the respondents said their service had adverts (N = 38). Participants also use ad blockers (N = 49). Just over a quarter of participants use cable T.V. (N = 27). When asked whether they pay for premium applications, the majority said ‘never’ (N = 60), occasionally (N = 16), sometimes (N = 9), usually (N = 2), whilst only one participant always pays for premium applications (N = 1). \r\nMATERIALS \r\nFirstly, two product categories were chosen, bottled water and soap bars, four brands were then selected per category (see table 1). There were 16 advertisements in total, eight for the simple and complex conditions, respectively. (APPENDIX A) The editing software Gimp was used to design the advertisements to enable the selected products to be presented in the controlled advert setting. This 'controlled setting' ensured that the backgrounds were consistent across the adverts, e.g., they all used the same blue background. Additionally, no text or fonts were added, and the objects included had the same position as their counterparts. There were two experimental groups wherein participants were presented the advertisements. Within those two groups participants would view one of the product categories e.g., the water products. To account for confounding variables advertisements were counterbalanced, randomizing their order of appearance. Participants only saw one product category (e.g., soap or water) and one variation of the advert e.g., if they saw the simple A1 Aveeno advert, they were not be presented with the complex B1 Aveeno advert. If participants saw the complex B5 Buxton advert, they were not presented with the simple B1 Buxton version. If participants saw the soap adverts, they did not see the water and vice versa.\r\nThe web-based software Qualtrics was used to create the surveys (APPENDIX B) and a generalized report of the results. After extracting the data, SPSS was used to dummy code and manipulate the data to measure the effect of visual complexity on recall. \r\nDESIGN \r\nThis experiment used a between-group design wherein participants were allocated either the simple or complex condition to examine which level of complexity had the larger effect (Turkeltaub et al., 2011). The type of complexity, simple or complex, is the independent variable of the experiment. The dependent variable is the effect this has on participants' recall (Atinc et al., 2011). In this project, simple advertisements are defined by having only one object included in the background, whereas complex advertisements are defined by having three objects. \r\nParticipants were first asked questions pertaining to free recall of product attributes before then being presented with the cued recall questions. This was to allow a distinction between non prompted (free) and prompted (cued) responses, enabling me to mark each survey and allocate a combined percentage recall score to each participant. \r\nTo control for confounding variables, the surveys were counterbalanced. Participants were shown the adverts randomly within each experimental group so that I could isolate the sequence effects that participants are exposed to. However, I could not control for extraneous variables such as the time of day participants completed the survey, their emotional state, or their level of intelligence. Additionally, situational factors such as the location they were in, e.g., whether the room they were in was too loud, too hot, too cold, could not be accounted for. \r\nTo prevent participants from rehearsing the material, distraction tasks were provided before requesting question responses (APPENDIX C). These were designed to be cognitively engaging by requiring participants to read sections of text and 'fill in' the missing words and select the 'odd word out' in a listing task. When completing these tasks, participants would not necessarily be aware that they were not an essential part of the study and thus, in processing their responses, would have to pause. For example, 'which word does not belong with the others?' had the response options of ‘Dog’, ‘Cat’, ‘Donkey’, and ‘Dragon’. There are actually two responses that could be deemed correct; however, participants are told to select one. The correct responses were ‘Cat’ as it is the only word beginning with the letter 'C' and ‘Dragon’ as it is the only creature with wings. Participants could not advance to the next section if there were any responses left blank. \r\nAll of the advertisements had the same consistent blue background, no fonts were used, and all objects had the same positioning between the simple and complex conditions. For example, A2 and B2 Dove both had the blue ribbon object included in the same position. All simple advertisements had one object; all complex advertisements had three objects to allow a comparison of the effect of complexity on consumers' explicit recall. \r\nPROCEDURE \r\nParticipants were found and randomly allocated to one of the experimental groups. They were first presented with the participant information sheet (APPENDIX D) in which general information about the experiment was explained without revealing that it was the level of complexity being measured. Participants were also required to complete the consent form. (APPENDIX E) Thus ensuring the participant is aware that their data will be collected anonymously and that they have the right to withdraw at any time should they please. \r\nParticipants then viewed four advertisements for 30 seconds per advert. They were not able to advance to the next image until the timer ended . The counterbalancing of questionnaires meant that the adverts were viewed in random orders. The distraction task then engaged participants for a few minutes as they could not advance until the distraction tasks were complete. \r\nParticipants were then asked the free recall questions in which they are expected to list the brands they can remember and list the product attributes for said brands. The soap category had 26 points available for free recall, and the water category had 15 points available. This is due to more attributes generally being included on the packaging of the soap comparatively to a generic product like water. Ergo, a more comprehensive list of features was able to be asked. \r\nOnce the participant had submitted the free recall section, they moved onto the cued recall questions. This section provided prompts in the questions, for example, ‘name the products, if any, that were moisturizing?’ participants may not have been able to recall this attribute freely. Therefore, these questions had to be presented separately so as not to influence each other. Furthermore, the free recall had to be asked first for the same reason of not influencing responses. If participants had filled the cued responses first, this would invalidate any free recall questions which may have followed. The soap and water categories respectively had 16 points available for the cued recall questions. \r\nOnce the survey was completed, participants were shown the debrief sheet (APPENDIX F) in which the aim of the study was fully explained, and they were provided with details should they have any questions about their role and wish to discuss it further. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2875"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2876"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2877"},["text","Proctor2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2878"},["text","Lydia Brooks"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2879"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2880"},["text","Field of visual complexity"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2881"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2882"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2883"},["text","LA1 4YW"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2884"},["text","Sally Linkenauger "]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2885"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2886"},["text","Cognitive, Perception; Marketing"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2887"},["text","88"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2888"},["text","ANOVA; T-Test"]]]]]]]]]